Engineer, Machine Learning

Link Logistics Real Estate (“Link”) is a leading operator of last-mile logistics real estate. Established by Blackstone in 2019, the company connects consumption, technology, and the supply chain across its portfolio, which spans more than half a billion square feet. With more than 5 percent of U.S. GDP flowing through our spaces, we leverage our scale, proprietary data and insights, and foundational focus on sustainability to drive success for our customers’ businesses and deliver value for our stakeholders. Link Logistics strives to be the most equitable and inclusive industrial real estate company in the business. We put our people, customers, and communities first and find ways to make a conscious, positive impact where we live and work, prioritizing diversity, equity and inclusion (DEI) across our workforce to deliver an optimal employee experience. Every day, we work to reinvent and lead our industry forward by thinking bigger and challenging the status quo. 

Because we believe that good business must be synonymous with doing good, strong environmental, social and governance practices are foundational to our identity as a firm. These practices include setting ambitious goals to combat climate change, partnering with local nonprofits, and prioritizing internal diversity, equity, and inclusion efforts. We seek to use our position, ideas, and influence to drive progress in our industry and the wider world.  At Link, we give our customers space to grow—and we give people space to grow, too. 

As a Machine Learning Engineer, your primary responsibilities will be to productionize supervised and unsupervised models, as well as advanced analytics.  You are conversant in several standard machine learning algorithms.  You are comfortable optimizing pipelines, reorganizing or rewriting code for ML and AI, evaluating cluster handling, and algorithmic performance and reliability.   You collaborate with our Customer Experience and Innovation teams, Sustainability team and Research team to make their work real for the business.

RESPONSIBILITIES:

• Implement and manage MLOps practices to automate and streamline the machine learning lifecycle, ensuring fast and reliable ML model deployment and monitoring.

• Monitor, update, and maintain the performance and reliability of deployed models.

• Implement testing and validation processes to ensure the reliability and effectiveness of models.

• Work hand-in-hand with Data Scientists and other teams to productionize their ML and analytical solutions.

• Collaborate with the Customer Experience, Research and Sustainability teams, as well as data engineers and other analysts.

• Proactively bring your experience to bear in conversation with technical and non-technical stakeholders.

QUALIFICATIONS:

• Experience ~3-5 years of success in ML/AI and production pipelines and in employing MLOps tools and practices.

• Monitoring Skills Experience with metric building, monitoring and maintaining ML pipelines in production environments.

• Technical Proficiency Deep expertise in Python, Spark, Spark Scala, or R. Experience with scalable distributed systems.

• Problem Solving. Ability to identify technical hurdles, and proactively build or suggest solutions.

• Collaboration and Communication. Acknowledged for driving decisions collaboratively, resolving conflicts and ensuring follow through with exceptional verbal and written communication skills.

Technical

Technical experience with production pipelines: 

• Deep expertise in some combination of these languages Python, Pyspark, Spark Scala, R

• Hands-on experience with ML frameworks (e.g. TensorFlow, Scikit-learn, etc)

• Strong SQL skills for querying databases, performing data analysis, and generating insights. Experience with scalable distributed systems (e.g. Databricks, Spark)

• Experience with MLOps tools and platforms to automate ML workflows. Strong SQL skills for querying databases, performing data analysis, and generating insights. Experience using cloud platforms such as MS Azure

• Monitoring and maintenance of ML pipelines

Education

• Masters Preferred

• Bachelor's degree in Computer Science, Data Science, Statistics, or related field, or equivalent work experience.

$175,000 - $195,000 represents the presently anticipated base compensation pay range for this position at Link.  Actual pay may vary based on various factors, including but not limited to location and experience.  

Link provides a variety of benefits to employees, including health insurance coverage, retirement savings plan, paid holidays, paid time off.

The direct compensation and benefits described above are subject to the terms and conditions of any governing plans, policies, practices, agreements, or other materials or documents as in effect from time to time, including but not limited to terms and conditions regarding eligibility.

EEO Statement

The Company is an equal opportunity employer. In accordance with applicable law, we prohibit discrimination against any applicant, employee, or other covered person based on any legally recognized basis, including, but not limited to: veteran status, uniformed servicemember status, race, color, caste, immigration status, religion, religious creed (including religious dress and grooming practices), sex, gender, gender expression, gender identity, marital status, sexual orientation, pregnancy (including childbirth, lactation or related medical conditions), age, national origin or ancestry, citizenship, physical or mental disability, genetic information (including testing and characteristics), protected leave status, domestic violence victim status, or any other consideration protected by federal, state or local law. We are committed to providing reasonable accommodations, if you need an accommodation to complete the application process, please email People@linklogistics.com.